For those of you into open source microscopy and imaging, the Engineering Biology Interdisciplinary Research Centre that I co-chair at the University of Cambridge has a forum on Tue 31 Jan that is free to attend online (or in person!) and will feature a talk from Ricardo Henriques on “Open-technology for Super-Resolution and Machine-Learning enabled Live-Cell BioImaging”
More details below and registration is via Eventbrite
I hope some of you can make it!
The Engineering Biology Forums are a series of talks exploring key tools for the future of engineering biology and biotechnology. Hosted by the Engineering Biology Interdisciplinary Research Centre at the University of Cambridge, the forums will take place Thursdays, 5pm-9pm at the Old Divinity School, St Johns College, Cambridge. Keynote lectures and discussion session will be followed by food, drinks and a fair including demonstrations, exhibitions and information showcasing scientific excellence from around the Cambridge engineering biology community.
Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
Title: MINFLUX nanoscopy and related matters
I will show how an in-depth description of the basic principles of diffraction-unlimited fluorescence microscopy (nanoscopy) [1-3] has spawned a new powerful superresolution concept, namely MINFLUX nanoscopy . MINFLUX utilizes a local excitation intensity minimum (of a doughnut or a standing wave) that is targeted like a probe in order to localize the fluorescent molecule to be registered. In combination with single-molecule switching for sequential registration, MINFLUX [4-7] has obtained the ultimate (super)resolution: the size of a molecule. MINFLUX nanoscopy, providing 1–3 nanometer resolution in fixed and living cells, is presently being established for routine fluorescence imaging at the highest, molecular-size resolution levels. Relying on fewer detected photons than popular camera-based localization, MINFLUX and related MINSTED [8,9] nanoscopies are poised to open a new chapter in the imaging of protein complexes and distributions in fixed and living cells. MINFLUX is also set to transform the single-molecule analysis of dynamic processes, as already demonstrated by tracking in detail the unhindered stepping of the motor protein kinesin-1 on microtubules at up to physiological ATP concentrations , and providing answers to longstanding questions with respect to the kinesin-1 mechanochemical cycle.
Stefan W. Hell is a director at both the Max Planck Institute for Multidisciplinary Sciences in Göttingen and at the Max Planck Institute for Medical Research in Heidelberg, Germany. He is credited with having conceived, validated and applied the first viable concept for breaking Abbe’s diffraction-limited resolution barrier in a light-focusing microscope and has received several awards: he shared the 2014 Kavli Prize in Nanoscience and the 2014 Nobel Prize in Chemistry. In 2022 Hell was admitted to the “Order Pour le Mérite"
Instituto Gulbenkian de Ciência, Oeiras, Portugal
Title: Open-technology for Super-Resolution and Machine-Learning enabled Live-Cell BioImaging
Computational analysis has become an essential part of microscopy, enabling and enhancing quantitative imaging approaches. Several cutting-edge microscopy methods now depend on an analytical step to process large volumes of recorded data, extract analytical information, and produce a final rendered image. Single-molecule localization-based super-resolution microscopy is a notorious example. In recent years, our team and collaborators have built an open-source ecosystem of combined computational and optical approaches particularly dedicated to improving live-cell microscopy, super-resolution imaging, and helping researchers retrieve high-fidelity quantitative data from their images. This talk will present some of the recent technologies we have recently developed. First, I will introduce ZeroCostDL4Mic, an entry-level platform simplifying the application of Deep-Learning (DL) analysis to biological microscopy images, by exploiting free openly-accessible cloud-based computational resources. ZeroCostDL4Mic allows researchers with no coding expertise to train and apply key DL tasks to perform segmentation, object detection, denoising, super-resolution microscopy, and microscopy modality image-to-image translation. We’ll demonstrate the application of the platform to study multiple biological processes, including in eucaryotic and procaryotic cells, and to analyze SMLM data. Next, I will cover recent development we have created for super-resolution microscopy through the NanoJ platform, highlighting the new “enhanced Super-Resolution Radial Fluctuations” (eSRRF) approach and its combination with real-time controlled microfluidics live-to-fix cell imaging, dubbed NanoJ-Fluidics, as well as real-time quality control on the predicted superresolution images via the SQUIRREL.
Prof. Ricardo Henriques is a group leader at Instituto Gulbenkian de Ciência, moving his laboratory in 2020 from University College London and Francis Crick Institute in the UK. His group uses optical and computational biophysics to study cell biology and host-pathogen interactions. He graduated in Physics, specialising in biophotonics and robotics. He finished his PhD in 2011, where he developed super-resolution microscopy technologies at the Musa Mhlanga lab. He then pursued postdoc research at Institut Pasteur Paris, studying HIV-1 T-cell infection through nanoscale imaging in the Christophe Zimmer lab.